package org.example.apitest.state;

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.checkpoint.ListCheckpointed;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.example.apitest.beans.SensorReading;

import java.util.Collections;
import java.util.List;

public class StateTest1OperatorState {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        env.getConfig().setAutoWatermarkInterval(100);

        // 从socket中读取数据
        DataStream<String> inputStream = env.socketTextStream("localhost", 7777);

        // 转换为SensorReading类型
        DataStream<SensorReading> dataStream = inputStream
                .map((MapFunction<String, SensorReading>) SensorReading::new);

        // 定义一个有状态的map操作,统计当前分区数据个数
        SingleOutputStreamOperator<Integer> resultStream = dataStream.map(new MyCountMapper());

        resultStream.print();

        env.execute();
    }

    public static class MyCountMapper implements MapFunction<SensorReading, Integer>, ListCheckpointed<Integer> {
        // 定义一个本地变量,作为算子状态
        private Integer count = 0;

        @Override
        public Integer map(SensorReading value) throws Exception {
            ++count;
            return count;
        }

        @Override
        public List<Integer> snapshotState(long checkpointId, long timestamp) throws Exception {
            return Collections.singletonList(count);
        }

        @Override
        public void restoreState(List<Integer> state) throws Exception {
            for (Integer num : state) {
                count = num;
            }
        }
    }
}
